Nowadays, vehicles are equipped with Advanced Driver Assisted Systems (ADAS) to provide assistance while driving a vehicle. One of the popular and highly useful ADAS in the recent times is surround view generation feature. The surround view provides a top-view or a bird's eye view of the vehicle along with coverage of 360-degree surrounding area of the vehicle. The surround view provides a view of the exterior of the vehicle on a display associated with the vehicle, to assist driver of the vehicle in manoeuvring the vehicle and also alerts the driver regarding obstacles along its path that may not be immediately visible. This feature helps in avoiding collisions with nearby vehicles on the road and also with other vehicles while parking in tight spaces.
One of the main requirements to generate an accurate surround view is to capture clear images of the surroundings of the vehicle in real-time. However, image capturing devices that capture the images are generally configured on external surface of the vehicle, due to which the image capturing devices may be exposed to environmental factors such as smoke, dirt, water and the like. There exists a high probability that, lenses of the image capturing devices could be covered partially or completely by dirt, water, and the like which affects clarity of images and creates certain occluded regions in the images. Due to such occluded regions in the images, surround view may not be generated accurately, which would subsequently affect the assistance provided to the driver.
Existing techniques provide techniques where images obtained by multiple image capturing devices of overlapping field of view may be used to remove occluded regions in the images caused by external objects such as other vehicles, mirrors of the vehicles, and the like. However, the images obtained from the multiple image capturing devices of overlapping field of view would be redundant and would involve processing of multiple images, thereby increasing the Turn Around time (TAT) for removing the occluded regions and also would lead to high utilization of resources. Further, if lenses of the multiple image capturing devices with overlapping field of view are covered with dust or water, the existing techniques may not be able to detect the occluded regions.